documentation: kwargs descriptions include clickable links (#1942)

Author: metrizable

src/sagemaker/model.py

@@ -791,7 +791,8 @@ def __init__(
                 authentication if they are provided; otherwise, python SDK will
                 try to use either CodeCommit credential helper or local
                 credential storage for authentication.
-            **kwargs: Keyword arguments passed to the ``Model`` initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/mxnet/model.py

@@ -107,8 +107,9 @@ def __init__(
             model_server_workers (int): Optional. The number of worker processes
                 used by the inference server. If None, server will use one
                 worker per vCPU.
-            **kwargs: Keyword arguments passed to the ``FrameworkModel``
-                initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/pytorch/model.py

@@ -75,7 +75,7 @@ def __init__(
         model_server_workers=None,
         **kwargs
     ):
-        """Initialize an PyTorchModel.
+        """Initialize a PyTorchModel.
 
         Args:
             model_data (str): The S3 location of a SageMaker model data
@@ -106,8 +106,9 @@ def __init__(
             model_server_workers (int): Optional. The number of worker processes
                 used by the inference server. If None, server will use one
                 worker per vCPU.
-            **kwargs: Keyword arguments passed to the ``FrameworkModel``
-                initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/tensorflow/model.py

@@ -175,7 +175,9 @@ def __init__(
                 to call to create a predictor with an endpoint name and
                 SageMaker ``Session``. If specified, ``deploy()`` returns the
                 result of invoking this function on the created endpoint name.
-            **kwargs: Keyword arguments passed to the ``Model`` initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/xgboost/model.py

@@ -90,7 +90,9 @@ def __init__(
                 created endpoint name.
             model_server_workers (int): Optional. The number of worker processes used by the
                 inference server. If None, server will use one worker per vCPU.
-            **kwargs: Keyword arguments passed to the ``FrameworkModel`` initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::